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Two-Dimensional Embeddings for Low-Resource Keyword Spotting Based on Dynamic Time Warping | Synapse
March 3, 2026
Two-Dimensional Embeddings for Low-Resource Keyword Spotting Based on Dynamic Time Warping
KW
Kevin Wilkinghoff
AC
Alessia Cornaggia-Urrigshardt
FG
Fahrettin Gökgöz
Key Points
Enhanced keyword spotting accuracy achieved through dynamic time warping techniques.
Performance metrics indicate significant improvements with two-dimensional embeddings in low-resource environments.
Analysis incorporates machine learning algorithms to optimize feature extraction for keywords.
Findings highlight the potential for better speech recognition systems in underserved contexts.
Abstract
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Wilkinghoff et al. (Fri,) studied this question.
synapsesocial.com/papers/69a75b9bc6e9836116a2336f
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